Combining hypoxia-activated prodrugs and radiotherapy in silico: Impact of treatment scheduling and the intra-tumoural oxygen landscape
| dc.contributor.author | Hamis, Sara | |
| dc.contributor.author | Kohandel, Mohammad | |
| dc.contributor.author | Dubois, Ludwig J. | |
| dc.contributor.author | Yaromina, Ala | |
| dc.contributor.author | Lambin, Philippe | |
| dc.contributor.author | Powathil, Gibin G. | |
| dc.date.accessioned | 2026-05-06T18:07:26Z | |
| dc.date.available | 2026-05-06T18:07:26Z | |
| dc.date.issued | 2020-08-03 | |
| dc.description | © 2020 Hamis et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. | |
| dc.description.abstract | Hypoxia-activated prodrugs (HAPs) present a conceptually elegant approach to not only overcome, but better yet, exploit intra-tumoural hypoxia. Despite being successful in vitro and in vivo, HAPs are yet to achieve successful results in clinical settings. It has been hypothesised that this lack of clinical success can, in part, be explained by the insufficiently stringent clinical screening selection of determining which tumours are suitable for HAP treatments. Taking a mathematical modelling approach, we investigate how tumour properties and HAP-radiation scheduling influence treatment outcomes in simulated tumours. The following key results are demonstrated in silico: (i) HAP and ionising radiation (IR) monotherapies may attack tumours in dissimilar, and complementary, ways. (ii) HAP-IR scheduling may impact treatment efficacy. (iii) HAPs may function as IR treatment intensifiers. (iv) The spatio-temporal intra-tumoural oxygen landscape may impact HAP efficacy. Our in silico framework is based on an on-lattice, hybrid, multiscale cellular automaton spanning three spatial dimensions. The mathematical model for tumour spheroid growth is parameterised by multicellular tumour spheroid (MCTS) data. | |
| dc.description.sponsorship | Medical Research Council, MR/R017506/1 || Swansea University PhD Research Studentship || Canadian Institutes of Health Research (CIHR) || European Research Council (ERC), advanced grant ERC-ADG-2015, n 694812 - Hypoximmuno || EUROSTARS, COMPACT 12053. | |
| dc.identifier.uri | https://doi.org/10.1371/journal.pcbi.1008041 | |
| dc.identifier.uri | https://hdl.handle.net/10012/23228 | |
| dc.language.iso | en | |
| dc.publisher | Public Library of Science | |
| dc.relation.ispartofseries | PLoS Computational Biology; 16(8); e1008041 | |
| dc.rights | Attribution 4.0 International | en |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | |
| dc.subject | cancer treatment | |
| dc.subject | malignant tumors | |
| dc.subject | hypoxia | |
| dc.subject | oxygen | |
| dc.subject | cancers and neoplasms | |
| dc.subject | radiation therapy | |
| dc.subject | medical hypoxia | |
| dc.subject | pro-drugs | |
| dc.title | Combining hypoxia-activated prodrugs and radiotherapy in silico: Impact of treatment scheduling and the intra-tumoural oxygen landscape | |
| dc.type | Article | |
| dcterms.bibliographicCitation | Hamis S, Kohandel M, Dubois LJ, Yaromina A, Lambin P, Powathil GG (2020) Combining hypoxia-activated prodrugs and radiotherapy in silico: Impact of treatment scheduling and the intra-tumoural oxygen landscape. PLoS Comput Biol 16(8): e1008041. https://doi.org/10.1371/journal.pcbi.1008041 | |
| uws.contributor.affiliation1 | Faculty of Mathematics | |
| uws.contributor.affiliation2 | Applied Mathematics | |
| uws.peerReviewStatus | Reviewed | |
| uws.scholarLevel | Faculty | |
| uws.typeOfResource | Text | en |